Staff Software Engineer, Inference Performance Optimization, GenAI, DeepMind

Google; Town of Montana (WI); On-site; USD 207,000 - 300,000; Full time

Benefits offered by this job

Bonus target

Equity

Job summary

Google DeepMind is hiring a Staff Software Engineer to optimize AI inference performance at scale. You will analyze the entire inference stack, implement optimization techniques, and drive systemic improvements to maximize throughput and reduce cost per inference.

You will collaborate with ML and systems teams on a range of AI agents and research prototypes. The role emphasizes end-to-end performance engineering, profiling workloads, and building instrumentation to guide capacity and latency

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of software development experience.
• Experience with Python and C++, including navigating and debugging serving codebases.
• Experience with AI model execution constraints, throughput-latency tradeoffs, memory bandwidth, and modern serving architectures.

Responsibilities

• Analyze and optimize AI inference workloads to increase throughput-per-GPU and reduce latency.
• Design and implement inference optimization techniques.
• Investigate and resolve complex model inference bottlenecks across the stack.
• Model latency-to-cost impacts and translate insights into production signals.
• Develop tools and metrics to track compute spend across the fleet.

Skills

Python

C++

Serving codebases

Performance optimization

Education

Bachelor's degree in CS/CE/EE or related field

Tools

vLLM

TensorRT-LLM

SGLang

Dynamo

Job description

Staff Software Engineer, Inference Performance Optimization, GenAI, DeepMind

Location

Mountain View, CA, USA

Minimum qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a related technical field, or equivalent practical experience.
• 8 years of experience in software development.
• Experience in Python and C++, including navigating, debugging, and modifying serving codebases.
• Experience with AI model execution constraints, throughput-latency tradeoffs, memory bandwidth limitations, and modern serving architectures.

Preferred qualifications

• Experience with real world LLM inference serving environments or direct contributions to modern open-source inference frameworks (e.g., vLLM, TensorRT-LLM, SGLang, Dynamo).
• Experience profiling workloads using standard ML profilers (e.g., PyTorch profiler) and internal trace analysis tools.
• Experience with observability and reliability for large distributed systems.
• Familiarity with GPU/TPU/accelerator performance concepts (e.g. memory bandwidth, quantization, collective communication, kernel), and can reason their implications to the overall inference serving performance.

About the job

At Google DeepMind, our mission is to build the world's first general-purpose learning agent. Central to this mission is the complex task of measuring the intelligence of our prototypes. As a Software Engineer, you will be working with the cutting-edge AI agents developed by our exceptional team of Machine Learning and Neuroscience research scientists. Your responsibilities will include everything from creating systems for agent testing using 2D and 3D games to developing test problems within physics simulators. You will create graphical visualizations of results, build competitive agent leaderboards and test new algorithms on robots. To succeed in this role, you will need to have a strong foundation in software engineering and enjoy working on a wide range of challenging problems within a mission-driven team.

As an Inference Performance Engineer, you will push the boundaries of AI model execution at scale. In this role, you will be at the forefront of making large-scale AI inference faster, cheaper, and more efficient. You will analyze the entire inference stack to identify critical bottlenecks and drive systemic improvements. By combining deep systems profiling, benchmarking, and first-principles problem solving, your work will directly maximize hardware throughput, reduce cost-to-serve, and empower our cross-functional teams to make data-driven capacity and latency tradeoffs.

Artificial intelligence will be one of humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207,000 - $300,000 (USD) + 20% bonus target + equity + benefits

Responsibilities

• Analyze and optimize AI inference workloads across the application, model, and distributed fleet infrastructure layers to methodically increase throughput-per-GPU and reduce latency.
• Design and implement inference optimization techniques.
• Investigate and resolve complex model inference performance bottlenecks across the stack.
• Model the latency-to-cost impacts of system variables (such as batch-sizing and utilization goals) and translate these insights into actionable signals that drive production systems.
• Develop investigative tools and metrics (e.g., compute/FLOPs funnels) that track where compute is spent across the fleet.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Locations

Mountain View, CA, USA